Application of HFPSO-TOPSIS approach for optimally locating and sizing of reactive power compensating devices for voltage control ancillary service

Author:

Kurundkar Kalyani1,Vaidya Dr. G.A.1

Affiliation:

1. PVG’s COET and GKP(W)IOM, India

Abstract

Modern power system with renewables in distribution network has made the optimal sizing and location of reactive power support crucial and essential. By optimal locating and sizing of reactive power support resources causes a power loss reduction, improvement in voltage profile and maximizes techno-economic benefits to consumers and system operators while improving overall system performance and reliability. However, the optimal location of the reactive power supporting device (OLRPSD) and its sizing for voltage control ancillary service is a multi-objective problem requiring a multi-objective multi-criteria decision-making (MOMCDM) approach. In literature, objectives of reactive power supporting have been to minimize the power losses. But it has more than one objective that depends upon the reactive power supporting device. Moreover, the economic benefit from reactive power support also requires to be considered, which is of utmost importance for all stakeholders. In this paper, OLRPSD is performed considering financial benefit by an objective of reactive power cost minimization along with other targets like power loss reduction, maximization stability margin of voltage, and minimization of deviation of voltage with an application of a recently developed MOMCDM technique known as Hybrid Firefly Particle Swarm Optimization with TOPSIS approach (HFPSO-TOPSIS) and is therefore new. This is executed on “modified IEEE 33 bus” radial distribution network. Various reactive power compensating devices considered are Distributed generation (DG’s), Batteries, capacitors and D-STATCOM and Electric vehicle charging stations. The results show the merit of this method over the existing ones.

Publisher

FOREX Publication

Subject

General Earth and Planetary Sciences,General Environmental Science

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